Job Description
Qualifications
10+ years of professional software engineering experience, with at least 5 years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model
Solid experience in the development and optimization of machine learning infrastructure tools like DeepSpeed, PyTorch, TensorFlow, or similar frameworks
Strong expertise in distributed training techniques, including gradient sharding and optimization strategies for scaling large models across ML accelerator profiling tools to uncover performance bottlenecks
Able to lead software development projects using C++ or Python and deploying on cloud platforms such as GCP, AWS, or Azure
Deep understanding of state-of-the-art machine learning models such as autoregressive transformers and familiarity with custom-kernels for diverse h/w compute based efficiency
Strong leadership skills with experience navigating cross-functional teams and providing technical leadership projects across multiple organizations
Excellent communication skills, both verbal and written, with the ability to translate complex technical concepts for a broad audience
We Prefer
Benefits
The expected base salary range for this full-time position across US locations is listed below
Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level
Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements
$272,000—$346,000 USD
Responsibilities
Technical Leadership - Provide deep technical leadership on large-scale ML model architectures, especially for autonomous vehicle models
Guide architectural decisions and technical direction for data, training, and deployment
Own large, complex systems, driving architectures that meet technical and business objectives
Distributed ML System: Design and scale large distributed systems covering the ML lifecycle, supporting planet-scale dataset generation and model training
Requirements Analysis: Collaborate cross-functionally to derive performance and system-level requirements for large ML systems
Translate product/business goals into measurable technical deliverables, ensuring system component alignment
Cross-Team Leadership: Guide efforts across teams and organizations to ensure seamless integration of data generation, model development, and deployment pipelines
Work at the intersection of data engineering, model development, and deployment, ensuring seamless integration and powering efficient innovation
Mentorship: Mentor junior engineers, growing their expertise and fostering a collaborative culture
Job description
Waymo is an autonomous driving technology company with the mission to be the most trusted driver. Since its start as the Google Self-Driving Car Project in 200+, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.
The Waymo ML Infrastructure team accelerates Waymo’s mission by building the best ecosystem for sustainably innovating and shipping ML-powered intelligence.
Our primary stakeholders are Research, Production, and Hardware teams, and our work powers state-of-the-art models in Perception and Planning, core to our autonomous driving software. We provide best-in-class solutions for the entire model development lifecycle, collaborating closely with Google teams. Scale and efficiency are core tenets.
We seek an experienced Senior IC to lead advanced AI infrastructure development for large-scale machine learning models (multi-billion parameter ML models), applying expertise in multi-sensor integration, massive model scaling, and distributed training. In this role
You Will
• Technical Leadership - Provide deep technical leadership on large-scale ML model architectures, especially for autonomous vehicle models. Guide architectural decisions and technical direction for data, training, and deployment. Own large, complex systems, driving architectures that meet technical and business objectives.
• Distributed ML System: Design and scale large distributed systems covering the ML lifecycle, supporting planet-scale dataset generation and model training.
• Requirements Analysis: Collaborate cross-functionally to derive performance and system-level requirements for large ML systems. Translate product/business goals into measurable technical deliverables, ensuring system component alignment.
• Cross-Team Leadership: Guide efforts across teams and organizations to ensure seamless integration of data generation, model development, and deployment pipelines. Work at the intersection of data engineering, model development, and deployment, ensuring seamless integration and powering efficient innovation.
• Mentorship: Mentor junior engineers, growing their expertise and fostering a collaborative culture.
You Have
• 10+ years of professional software engineering experience, with at least 5 years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model.
• Solid experience in the development and optimization of machine learning infrastructure tools like DeepSpeed, PyTorch, TensorFlow, or similar frameworks.
• Strong expertise in distributed training techniques, including gradient sharding and optimization strategies for scaling large models across ML accelerator profiling tools to uncover performance bottlenecks.
• Able to lead software development projects using C++ or Python and deploying on cloud platforms such as GCP, AWS, or Azure.
• Deep understanding of state-of-the-art machine learning models such as autoregressive transformers and familiarity with custom-kernels for diverse h/w compute based efficiency.
• Strong leadership skills with experience navigating cross-functional teams and providing technical leadership projects across multiple organizations.
• Excellent communication skills, both verbal and written, with the ability to translate complex technical concepts for a broad audience.
We Prefer
• A Master’s or PhD in Computer Science, Engineering, or a related field is preferred.
• Preferred experience includes on device ML.
This role reports to an Engineering Manager
#Hybrid
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Salary Range
$272,000—$346,000 USD
10+ years of professional software engineering experience, with at least 5 years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model
Solid experience in the development and optimization of machine learning infrastructure tools like DeepSpeed, PyTorch, TensorFlow, or similar frameworks
Strong expertise in distributed training techniques, including gradient sharding and optimization strategies for scaling large models across ML accelerator profiling tools to uncover performance bottlenecks
Able to lead software development projects using C++ or Python and deploying on cloud platforms such as GCP, AWS, or Azure
Deep understanding of state-of-the-art machine learning models such as autoregressive transformers and familiarity with custom-kernels for diverse h/w compute based efficiency
Strong leadership skills with experience navigating cross-functional teams and providing technical leadership projects across multiple organizations
Excellent communication skills, both verbal and written, with the ability to translate complex technical concepts for a broad audience
We Prefer
Benefits
The expected base salary range for this full-time position across US locations is listed below
Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level
Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements
$272,000—$346,000 USD
Responsibilities
Technical Leadership - Provide deep technical leadership on large-scale ML model architectures, especially for autonomous vehicle models
Guide architectural decisions and technical direction for data, training, and deployment
Own large, complex systems, driving architectures that meet technical and business objectives
Distributed ML System: Design and scale large distributed systems covering the ML lifecycle, supporting planet-scale dataset generation and model training
Requirements Analysis: Collaborate cross-functionally to derive performance and system-level requirements for large ML systems
Translate product/business goals into measurable technical deliverables, ensuring system component alignment
Cross-Team Leadership: Guide efforts across teams and organizations to ensure seamless integration of data generation, model development, and deployment pipelines
Work at the intersection of data engineering, model development, and deployment, ensuring seamless integration and powering efficient innovation
Mentorship: Mentor junior engineers, growing their expertise and fostering a collaborative culture
Job description
Waymo is an autonomous driving technology company with the mission to be the most trusted driver. Since its start as the Google Self-Driving Car Project in 200+, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.
The Waymo ML Infrastructure team accelerates Waymo’s mission by building the best ecosystem for sustainably innovating and shipping ML-powered intelligence.
Our primary stakeholders are Research, Production, and Hardware teams, and our work powers state-of-the-art models in Perception and Planning, core to our autonomous driving software. We provide best-in-class solutions for the entire model development lifecycle, collaborating closely with Google teams. Scale and efficiency are core tenets.
We seek an experienced Senior IC to lead advanced AI infrastructure development for large-scale machine learning models (multi-billion parameter ML models), applying expertise in multi-sensor integration, massive model scaling, and distributed training. In this role
You Will
• Technical Leadership - Provide deep technical leadership on large-scale ML model architectures, especially for autonomous vehicle models. Guide architectural decisions and technical direction for data, training, and deployment. Own large, complex systems, driving architectures that meet technical and business objectives.
• Distributed ML System: Design and scale large distributed systems covering the ML lifecycle, supporting planet-scale dataset generation and model training.
• Requirements Analysis: Collaborate cross-functionally to derive performance and system-level requirements for large ML systems. Translate product/business goals into measurable technical deliverables, ensuring system component alignment.
• Cross-Team Leadership: Guide efforts across teams and organizations to ensure seamless integration of data generation, model development, and deployment pipelines. Work at the intersection of data engineering, model development, and deployment, ensuring seamless integration and powering efficient innovation.
• Mentorship: Mentor junior engineers, growing their expertise and fostering a collaborative culture.
You Have
• 10+ years of professional software engineering experience, with at least 5 years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model.
• Solid experience in the development and optimization of machine learning infrastructure tools like DeepSpeed, PyTorch, TensorFlow, or similar frameworks.
• Strong expertise in distributed training techniques, including gradient sharding and optimization strategies for scaling large models across ML accelerator profiling tools to uncover performance bottlenecks.
• Able to lead software development projects using C++ or Python and deploying on cloud platforms such as GCP, AWS, or Azure.
• Deep understanding of state-of-the-art machine learning models such as autoregressive transformers and familiarity with custom-kernels for diverse h/w compute based efficiency.
• Strong leadership skills with experience navigating cross-functional teams and providing technical leadership projects across multiple organizations.
• Excellent communication skills, both verbal and written, with the ability to translate complex technical concepts for a broad audience.
We Prefer
• A Master’s or PhD in Computer Science, Engineering, or a related field is preferred.
• Preferred experience includes on device ML.
This role reports to an Engineering Manager
#Hybrid
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Salary Range
$272,000—$346,000 USD
💡 Quick Summary
Seeking a career-building opportunity? The Senior Staff Software Engineer, ML Infrastructure position is now open for candidates interested in the IT Engineer & Developer Jobs sector. This role in Walla Walla offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in IT Engineer & Developer Jobs is a plus.
